Children and the Elderly: Wealth Inequality Among America’s Dependents

Life cycle theory predicts that elderly households have higher levels of wealth than households with children, but these wealth gaps are likely dynamic, responding to changes in labor market conditions, patterns of debt accumulation, and the overall economic context. Using Survey of Consumer Finances data from 1989 through 2013, we compare wealth levels between and within the two groups that make up America’s dependents: the elderly and child households (households with a resident child aged 18 or younger). Over the observed period, the absolute wealth gap between elderly and child households in the United States increased substantially, and diverging trends in wealth accumulation exacerbated preexisting between-group disparities. Widening gaps were particularly pronounced among the least-wealthy elderly and child households. Differential demographic change in marital status and racial composition by subgroup do not explain the widening gap. We also find increasing wealth inequality within child households and the rise of a “parental 1 %.” During a time of overall economic growth, the elderly have been able to maintain or increase their wealth, whereas many of the least-wealthy child households saw precipitous declines. Our findings suggest that many child households may lack sufficient assets to promote the successful flourishing of the next generation.     

Saving,Sharing, or Spending? The Wealth Consequences of Raising Children

This study uses 1986–2012 National Longitudinal Survey of Youth 1979 cohort data to investigate the relationship between raising children and net worth among younger Baby Boomer parents. I combine fixed-effects and unconditional quantile regression models to estimate changes in net worth associated with having children in different age groups across the wealth distribution. This allows me to test whether standard economic models for savings and consumption over the life course hold for families at different wealth levels. My findings show that the wealth effects of children vary throughout the distribution. Among families at or below the median, children of all ages were associated with wealth declines, likely due to the costs of child-rearing. However, at the 75th percentile and above, wealth increased with the presence of younger children but decreased after those children reached age 18. My results, therefore, provide evidence for a saving and investment model of child-rearing among wealthier families but not among families at or below median wealth levels. For these families, the costs of raising children largely outweighed motivations for saving.     

The Wealth of Nations and the Happiness of Nations: Why “Accounting” Matters

We review income-happiness research in light of competing theoretical frameworks, unit of analysis, and methodological issues. Within-countries, absolute income is weakly related to happiness, comparison effects depend on the measure utilized, and income change and perceived income produce inconsistent findings. Across countries, absolute income is a stronger predictor of happiness, different comparison effects are significant, income change results are predominantly positive, and the financial-life satisfaction relationship is more robust.     

Financial Satisfaction in Old Age: A Satisfaction Paradox or a Result of Accumulated Wealth?

Prior research consistently has found that older adults, despite low incomes, are more financially satisfied than younger adults. This “satisfaction paradox” is typically attributed to elders’ supposed psychological accommodation to poor financial circumstances. We advance a different explanation, one that focuses on substantial age differences in wealth and liabilities. Data are from the first wave of the Norwegian NorLAG study (n = 4,169). Findings support the hypothesis that an examination of a wider range of economic variables shows that material circumstances are more important to the financial satisfaction of the elderly than previously believed. A considerable part of the higher financial satisfaction with increasing age can thus be explained by greater assets and less debt among the aged. Nonetheless, assets and debt do not mediate this relationship at lower incomes, because older people with little income have very little accumulated wealth. As older people with little income and wealth have a much stronger tendency to be financially satisfied than their younger, equally poor counterparts, an “aging paradox” still remains in this field.     

Inequality, Wealth and Health: Is Decreasing Income Inequality the Key to Create Healthier Societies?

The idea that the level of stratification of societies contributes to the well-being of their members is gaining popularity. We contribute to this debate by investigating whether reducing inequalities in the income distribution of societies is a strategy for improving population health, especially appropriate for those countries that have reached the limits of economic growth. We test this idea on a dataset covering 140 countries and 2360 country-year observation between 1987 and 2008 and formulate hypotheses separately for countries with different level of economic development. We indeed found that countries with higher levels of income inequality also have lower levels of life expectancy (our measure of population health), and this result was consistent both in cross-sectional and longitudinal analyses. However, the relationship was found only among low- and middle-developed countries. In the group of high-developed countries, the relationship between income inequality and life expectancy was non-significant, which contradicts the literature. Expectations on the relationship between a country’s wealth and health were confirmed: economic growth does contribute to improving population health, but this effect is weaker in more economically developed countries. These results imply that a decrease in a country’s income inequality parallel with an increase in its wealth can help to improve health in economically lesser-developed countries, but not in high-developed countries.     

Do Racial Disparities in Private Transfers Help Explain the Racial Wealth Gap? New Evidence From Longitudinal Data

How do private transfers differ by race and ethnicity, and do such differences explain the racial and ethnic disparity in wealth? Using the Panel Study of Income Dynamics, this study examines private transfers by race and ethnicity in the United States and explores a causal relationship between private transfers and wealth. Panel data and a family-level fixed-effect model are used to control for the endogeneity of private transfers. Private transfers in the form of financial support received and given from extended families and friends, as well as large gifts and inheritances, are examined. We find that African Americans and Hispanics (both immigrant and nonimmigrant) receive less in both types of private transfers than whites. Large gifts and inheritances, but not net financial support received, are related to wealth increases for African American and white families. Overall, we estimate that the African American shortfall in large gifts and inheritances accounts for 12 % of the white-black racial wealth gap.     

Estimating Wealth Effects Without Expenditure Data—Or Tears: An Application To Educational Enrollments In States Of India*

Using data from India, we estimate the relationship between household wealth and children's school enrollment. We proxy wealth by constructing a linear index from asset ownership indicators, using principal-components analysis to derive weights. In Indian data this index is robust to the assets included, and produces internally coherent results. State-level results correspond well to independent data on per capita output and poverty. To validate the method and to show that the asset index predicts enrollments as accurately as expenditures, or more so, we use data sets from Indonesia, Pakistan, and Nepal that contain information on both expenditures and assets. The results show large, variable wealth gaps in children's enrollment across Indian states. On average a "rich" child is 31 percentage points more likely to be enrolled than a "poor" child, but this gap varies from only 4.6 percentage points in Kerala to 38.2 in Uttar Pradesh and 42.6 in Bihar.     

Money Does not Buy Happiness: Or Does It? A Reassessment Based on the Combined Effects of Wealth,Income and Consumption

The paper uses household economic panel data from five countries—Australia, Britain, Germany, Hungary and The Netherlands—to provide a reassessment of the impact of economic well-being on happiness. The main conclusion is that happiness is considerably more affected by economic circumstances than previously believed. In all five countries wealth affects life satisfaction more than income. In the countries for which consumption data are available (Britain and Hungary), non-durable consumption expenditures also prove at least as important to happiness as income.